Restructuring a Military Medical Department Research Center

Restructuring a Military Medical Department Research Center

W. F. Lawless (Paine College, USA), Joseph Wood (Fort Gordon, USA) and Hui-Lien Tung (Paine College, USA)
Copyright: © 2008 |Pages: 8
DOI: 10.4018/978-1-59904-889-5.ch148
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Abstract

This case study is of a military medical department research center (MDRC) with access to advanced information systems (IS), yet struggling to determine the quality of its residents in training and their scholarly productivity (see the article on “Theory Driven Organizational Metrics” in this encyclopedia). Based on theory, this case study was guided by stories captured from MDRC in the collapse of four interdependent variables: planning, execution, resources, and time. Our primary goals for this case study were to: (1) Formulate recommendations to utilize the IS available to reduce the overall operational cost of MDRC; (2) increase the operational efficiency and growth of MDRC by enhancing its ability to attract new extramural funds; and (3) further explore the link between practice and theory. To the extent possible, all organizational names, references, and locations have been revised to fictitious ones.

Key Terms in this Chapter

Measurement Problem/Paradox: Assuming the existence of uncertainty in the four interdependent variables of planning-execution and resources-time, decreasing the uncertainty in either set raises the uncertainty in its correspondingly linked interdependent variable.

Command Decision Making (CDM): Top-down decision-making, especially the autocratic decision-making practiced in industry, business, and the military, but also by dictators. CDM reduces innovativeness but increases productivity. Further, CDM often employs consensus rules in its decision-making processes, because CR is open to exploitation (Kruglanski et al., 2006).

Majority Rules (MR): Majority rules often lead to faster decisions, more practical decisions, and, counterintuitively, stronger consensuses. The problem with majority rules is that they introduce conflict into decision-making. But if the conflict can be moderated or managed, the result is more learning among the participants compared to consensus rules.

Metrics: The metrics for MDRC are being designed to convert the measurement problem into an organizational metric of performance.

Methodological Individualism (MI): Game theory (Nowak & Sigmund, 2004) has attempted to substantiate the superiority of cooperation, based on the belief that cooperation leads to the highest social good, even if it is coerced (Hardin, 1968). However, the lack of substantiating evidence in support of the social worth of cooperation is reviewed in Lawless and Grayson (2004).

Consensus-Seeking Rules (CR): By reducing evidentiary barriers to discussion, consensus-seeking rules often lead to the least common worldview amongst risk perceivers, making it unlikely to reach a practical decision other than to instantiate past organizational practices, but consequently, reducing innovativeness. Further, consensus rules require considerable time to listen to each risk perception.

Business Models (BM): A business model is a complex plan for business operations and strategy that, when it converges into a consensus, it maximizes productivity, but the stronger the consensus in support of the BM, the more that innovation is reduced. Alternatively, divergence increases opportunities for innovation, but by reducing productivity. This paradox is reduced by creating ambidextrous organizations that can operate in a state of tension between both increasing productivity and innovativeness (Smith & Tushman, 2005).

Agent-Based Model (ABM): Used to create complex models of organizations and systems; for example, with Monte Carlo methods, ABM’s can be designed to reduce biases in Critical Path Method (CPM models and Program Evaluation Review Technique [PERT]) models.

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